Biomedical Engineering Reference
In-Depth Information
this is a consequence of the openness and “fl exibility” allowing data to be
deposited from essentially any source and in a wide variety of formats. In that
sense PubChem has more of the characteristics of an open data repository and
less that of a data warehouse with defi ned terminology metadata. This was a
conscious choice when PubChem was set up, because the fast pace of innova-
tion in assay designs to interrogate complex biological processes using novel
detection technologies limits the effectiveness of “static” relational database
systems to capture and manage the diversity of screening experiments and
their outcomes. To effectively address these limitations, a semantic framework
with a bioassay ontology at its core is required.
During the last several years many biomedical “ontologies” have been
developed with the goal of describing and integrating complex biological
knowledge with existing databases [51] and advancing translational research
[52]. Many biomedical ontologies are available in the Open Biological and
Biomedical Ontologies (OBO) Foundry [53] with the most prevalent being
Gene Ontology (GO) [54, 55]. However, only a few of the other OBO onto-
logies are widely used, and there has been criticism about the lack of
international standards in many bio-ontologies from the Semantic Web com-
munity [56] .
More recently the semantic integration and annotation of small-molecule
data with existing biological databases have been reported [57, 58]. However—
until now—there is no comprehensive effort to develop an ontology to describe
the increasing body of HTS experiments and the data these experiments
produce. In particular, we are not aware of a standardized assay ontology that
is accessible to the neglected disease community. Collaborative software for
chemistry and biology data could have a direct impact on promoting the adop-
tion of such an ontology for neglected disease bioassay data. Adoption of an
open-assay ontology will be a major milestone in converting volumes of assay
data
into machine - interpretable
knowledge
and fi nally human
insight.
With PubChem and several other accessible screening data repositories
there is now a sizable publicly accessible corpus of screening experiments and
their results. This makes it possible for the fi rst time to develop a knowledge
representation of HTS assays and screening results in an open effort. Because
this corpus and its diversity are growing exponentially, the development of a
clearly structured and standardized formal description of the concepts that are
relevant to interpret HTS results is also very timely. To be successful in the
long term, such an assay ontology needs to be maintained and kept up to date
(much like GO), and there is also a need for ongoing bio-curation to system-
atically annotate the data sets.
28.4.1
BioAssay Ontology
BioAssay Ontology (BAO) [59] is an NIH-funded project to facilitate analysis
of screening results from large numbers of diverse biological screens spanning
various technologies (and originating from different sources). The BAO
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